In the capacity planning process, system parameters, desired service levels, and workload predictions are used to determine when the resources of a computer system will be exceeded and are used to assist in identifying cost-effective remedies to resource shortfalls. “Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems”, by Daniel A. Menasce, Virgilio A. Almeida, and Larry W. Dowdy (Prentice Hall, Englewood Cliffs, N.J., 1994) discloses approaches to both the predicting and rectifying of computer resource challenges.
Capacity planning for a set of heterogeneous computer systems presents several problems, as set forth below. As a first challenge, it must be recognized that workloads use multiple resources. Therefore, the effect of workload assignment is not readily predicted or quantified. Second, workload typically grows, and the rate of growth may differ between resources. Third, different computer systems may have different resources, and different resource capacities. These problems can make it difficult to determine how long available resources will last, which computer systems are most at risk for exceeding their resources, how to reallocate resources to alleviate shortages, and how the computer systems will be affected by such reallocations.
Dan Asit and Dinkar Sitaram, in U.S. Pat. No. 5,530,557, entitled “Online Placement of Video Files Determined by a Function of the Bandwidth to Space Ratio of each of the Storage Devices in a Server Environment”, (Jun. 25, 1996) teach one solution for maximizing storage utilization for the placement of videos on storage devices taking into account the expected demand for the video. Asit, et al use the bandwidth space ratio (BSR) to place videos on disks. The BSR of a disk is its bandwidth divided by space. The BSR of a video is the expected demand for the video divided by the space required to store it. Demand may be forecast based on historical usage data and, in their invention, a Video Placement Manager places the videos on the disks to match the BSR of the videos with the BSR of the disk.
Additional references which have sought to predict and manage storage capacity include an article and related patent application of W. G. Pope and Lily Mummert. The article entitled “The Use of Life Expectancy to Manage Notes Domino E-Mail Storage”, Proceedings of the Computer Measurement Group, CMG '99, December 1999, and the patent application Ser. No. 09/457,467 entitled “System and Method for Providing Property Histories of Objects and Collections For Determining Device Capacity Based Thereon”, which was filed on Dec. 8, 1999, propose a method for projecting device capacity by past history of access to and usage of the relevant information for a single computer system.
In general, the amount of workload on a computing system grows over time. Eventually, workload exceeds the system's capacity causing either unscheduled outages or severe performance degradation which results in increased administrative costs and reduced customer satisfaction. When the server is a member of a group of servers where workload can be moved to some other server in the group, it is desirable to avoid these problems with planned action, as will be addressed by the present invention.
The date when a server's workload exceeds its capacity is called its expiration date. An expiration date is established using the aforementioned methods like life expectancy or capacity space. To provide a quality service, it is necessary to upgrade or offload the server before its expiration date. Usually, there are certain key dates when major changes can be made to a server with minor impact to service. These dates are conventionally associated with holidays, whereby service impact is reduced if servers are upgraded on a key date that precedes the expiration date.
Other resources, such as administrative personnel, are normally in limited supply. This constraint bounds the number of server upgrades that can be performed on any given key date. Thus, it is necessary to distribute the expiration dates of servers to fit within the bounds dictated by these other resources. A system's expiration date can be adjusted by adding or removing workload.
What is needed is a system and method which analyzes the combined expiration dates of a group of systems and adjusts the location of workload to align the expiration dates of systems in the group with key dates in order to fit within the bounds dictated by external resources.
What is additionally needed is to provide a system and method for analyzing the impact of a single workload unit on the capacity of a system.
Another objective of the present invention is to utilize workload unit impact measurements to improve the life expectancies of as many of the processing systems in a processing environment as possible.